20240087341.ROBUST STATE ESTIMATION simplified abstract (nvidia corporation)
Contents
- 1 ROBUST STATE ESTIMATION
ROBUST STATE ESTIMATION
Organization Name
Inventor(s)
Yuzhuo Ren of Sunnyvale CA (US)
Niranjan Avadhanam of Saratoga CA (US)
ROBUST STATE ESTIMATION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240087341 titled 'ROBUST STATE ESTIMATION
Simplified Explanation
The patent application describes a method for determining the state of a subject, such as drowsiness, using facial landmarks and blink parameters.
- Facial landmarks are extracted from captured image data to determine blink parameters.
- Blink parameters are used in a temporal network to estimate the subject's state.
- An eye state determination network can determine eye state without relying on landmarks.
- The eye state information is used in another temporal network to estimate the subject's state.
- A weighted combination of these values provides an overall state of the subject.
- Individual behavior patterns and context information are utilized to improve accuracy.
Potential Applications
This technology can be applied in various fields such as driver monitoring systems, fatigue detection in workers, and healthcare for monitoring patient drowsiness.
Problems Solved
This technology addresses the issue of accurately determining the state of a subject, such as drowsiness, using facial landmarks and blink parameters, while accounting for variations in data due to subject variation or current context.
Benefits
The benefits of this technology include improved accuracy in determining the state of a subject, robustness to different inputs or conditions, and the ability to utilize individual behavior patterns and context information for better results.
Potential Commercial Applications
Potential commercial applications of this technology include integrating it into driver monitoring systems for automotive companies, fatigue detection systems for industries, and healthcare monitoring devices for patient safety.
Possible Prior Art
One possible prior art could be the use of facial recognition technology for monitoring drowsiness in subjects, but the specific method described in this patent application, utilizing facial landmarks and blink parameters in temporal networks, appears to be novel and innovative.
Unanswered Questions
How does this technology handle variations in lighting conditions during image capture?
The patent application does not specify how the technology accounts for variations in lighting conditions that may affect the accuracy of facial landmark extraction and blink parameter determination.
What is the computational complexity of the proposed method compared to existing techniques?
The patent application does not provide information on the computational complexity of the proposed method and how it compares to other techniques in terms of efficiency and processing speed.
Original Abstract Submitted
state information can be determined for a subject that is robust to different inputs or conditions. for drowsiness, facial landmarks can be determined from captured image data and used to determine a set of blink parameters. these parameters can be used, such as with a temporal network, to estimate a state (e.g., drowsiness) of the subject. to improve robustness, an eye state determination network can determine eye state from the image data, without reliance on intermediate landmarks, that can be used, such as with another temporal network, to estimate the state of the subject. a weighted combination of these values can be used to determine an overall state of the subject. to improve accuracy, individual behavior patterns and context information can be utilized to account for variations in the data due to subject variation or current context rather than changes in state.
